Adaptive Algorithms and Stochastic Approximations

Adaptation is now recognised as a keystone of "intelligence" within computerised systems. This book is a reference work, both for engineers who use stochastic approximations in terms of problems arising from real applications. Relevant application areas are adaptive filtering and more generally adaptive signal processing, systems identification and adaptive control, and several aspects of pattern recognition and machine intelligence.

Contenu
I. Adaptive Algorithms: Applications.- 1. General Adaptive Algorithm Form.- 2. Convergence: the ODE Method.- 3. Rate of Convergence.- 4. Tracking Non-Stationary Parameters.- 5. Sequential Detection; Model Validation.- 6. Appendices to Part I.- II. Stochastic Approximations: Theory.- 1. O.D.E. and Convergence A.S. for an Algorithm with Locally Bounded Moments.- 2. Application to the Examples of Part I.- 3. Analysis of the Algorithm in the General Case.- 4. Gaussian Approximations to the Algorithms.- 5. Appendix to Part II: A Simple Theorem in the Robbins-Monro Case.- Subject Index to Part I.- Subject Index to Part II.